Results 271 to 280 of about 380,414 (301)
Some of the next articles are maybe not open access.
The area under the generalized receiver-operating characteristic curve
The International Journal of Biostatistics, 2021Abstract The receiver operating-characteristic (ROC) curve is a well-known graphical tool routinely used for evaluating the discriminatory ability of continuous markers, referring to a binary characteristic. The area under the curve (AUC) has been proposed as a summarized accuracy index.
Pablo Martínez-Camblor +2 more
openaire +2 more sources
Confidence Bands for Receiver Operating Characteristic Curves
Medical Decision Making, 1993Receiver operating characteristic (ROC) curves are mapped out by the two types of errors that are generated by varying the decision threshold used to determine which subjects will be considered abnormal. Under the conventional binormal model for the ROC curve, two- sided and one-sided simultaneous confidence bands for an entire ROC curve, or for a ...
G, Ma, W J, Hall
openaire +2 more sources
Radiographic Applications of Receiver Operating Characteristic (ROC) Curves
Radiology, 1974The basic concepts underlying the theory and experimental determination of receiver operating characteristic (ROC) curves are discussed. Such curves were used to describe the detectability of the image of 2 mm Lucite beads (similar to certain small gallstones) in a noisy background of radiographic mottle. Results are shown for four typical radiographic
D J, Goodenough +2 more
openaire +2 more sources
Correcting for Confounding in Analyzing Receiver Operating Characteristic Curves
Biometrical Journal, 1996AbstractA method is described for modeling a receiver operating curve as a function of confounding covariates when the outcome of the screening test is a continuous variate. A parametric survival model is proposed for modeling the distribution of the screening test outcome as a function of true disease status and other confounding covariates.
Smith, P. J., Thompson, T. J.
openaire +1 more source
Receiver Operating Characteristic (ROC) Curves: The Basics and Beyond
Hospital PediatricsDiagnostic tests and clinical prediction rules are frequently used to help estimate the probability of a disease or outcome. How well a test or rule distinguishes between disease or no disease (discrimination) can be measured by plotting a receiver operating characteristic (ROC) curve and calculating the area under it (AUROC).
Pearl W, Chang, Thomas B, Newman
openaire +2 more sources
Comparison of the binormal and Lehman receiver operating characteristic curves
Communications in Statistics - Simulation and Computation, 2022Musie Ghebremichael, Haben Michael
openaire +1 more source
The area under the generalized receiver-operating characteristic curve
International Journal of Biostatistics, 2022Pablo Martínez-Camblor +2 more
exaly
The Generalized Receiver Operating Characteristic Curve
2016The problem is to predict whether a random outcome is a "success" (R=1) or a "failure" (R=0) given a continuous variable Z. The performance of a prediction rule $D=D(Z)\in \{1,0\}$ boils down to two probabilities, beta =Pr (D=1|R=1) and alpha =Pr (D=1|R=0). We wish beta is high, alpha is low. Given a set of rules D such that any d in D is attributed to
openaire +2 more sources
Minimum distance estimation of the Lehmann receiver operating characteristic curve
Statistics, 2021Alicja Jokiel-Rokita +1 more
exaly